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Mathematica. Which has this pretty complete collection of formal algorithms in areas like geometry, image processing [and many others]. We start with Mathematica, and we build onto it. Mathematica deals with pure knowledge, but there’s also very specific knowledge. (What is the actual approximation to the flow over an airfoil, for example.)

Wolfram Alpha is implemented in 7 million lines of code. There’s a lot more work to do. We try to always get to the frontier of what can be computed. We’re going to get it to the best it can be done. But in 2009, computers just aren’t fast enough to compute some pieces. [Compare 7 million lines to the four lines of code that Wolfram thinks might underlie the workings of the entire universe---Eds.]

X: Let’s step back for a minute. How is Wolfram Research doing financially?

SW: We have 600-something employees. I was shocked at how large our company Christmas party was. We’ve been lucky enough to be profitable for 21 years, since 1988. That’s the reason we were able to do Wolfram Alpha. If I had gone to venture capitalist friends of mine, I don’t know what would have happened. [See this account of what happened in his first company, which went the VC route---Eds.] This was all internally funded. This year, Mathematica has been doing really well. Maybe we do well in recessions because people think more then.

X: How is the partnership with Bing going? Will we see more deals with search engines and other websites?

SW: It’s in early days. We’re starting to see some Wolfram Alpha content showing up as part of the big search engine experience. I think there’s a nice complementarity with computable knowledge with what search engines are trying to do. Expect a bunch more things along those lines.

We have an API [application programming interface] starting to get used by a bunch of people. (It’s the basis for the Bing partnership and the Wolfram Alpha iPhone app). One thing coming out soon is the first step in a big arc of taking what we’ve done with Wolfram Alpha and merging it with the precise programming capabilities we have in Mathematica. The first thing will be a widget builder. Like a mortgage calculator, or the distance to the moon, or where I am on some medical distribution curve. Normally you do some work making a Web interface, but then the real hard work is to make the interface connect to something to do something. We’ve done that.

You publish a piece of Java script on a page, and there’ll be a widget you can type into and it connects to Wolfram Alpha. There’s a great intellectual problem which I haven’t completely solved: On one hand we have Wolfram Alpha that’s very, very broad and quick—I’ve got one question— and on the other hand we have Mathematica, that’s very precise and formulated in a way you can really build on. So the very interesting thing is, what’s between these two extremes? An example is future versions of Mathematica—where you can type free-form linguistics, and it turns into Mathematica formulations you can pick out. You type it in in English, and you get back a piece of code.

From a business point of view, there’s the API and deployment on lots of different devices and platforms and use in other programs. The widget builder is for anyone who’s building a business.

X: So what are the next big steps for Wolfram Alpha?

SW: It was a very difficult decision when we should release Wolfram Alpha into the wild. It had to be good enough for people to see where it was going. But we knew after it’s out in the wild, we’d have a better idea. We can analyze hundreds of millions of queries streaming through the thing. In linguistics, we can learn the language people use to make queries. Before that, we used Web corpuses. Now we’re in a position to really learn that. We can see what domains people expect us to have that we don’t yet have. That helps us prioritize our development work. It is notable to me that it’s never a pure “turn the crank” thing. You might think by the time you’ve done a few thousand domains, the next one will be easy. But always, some new issue comes up which requires a domain expert and some thought.

We’ve been expanding the domains we cover. The code base has grown. From a software engineering point of view, we have a smooth thing going. A new code base is released every week. Data feeds are being updated every second. We’re seeing evolution in Wolfram Alpha itself, and in the user base for how to use Wolfram Alpha. We can make the system adapt to the users, but also the users will change and adapt to us. It’s a co-evolution, in different professions—medicine, engineering. We’ll see more drilling [down] of those spaces.

We have a healthy volunteer network of people helping us with all kinds of data questions, helping us analyze anomalies in data. I expect that will grow. It’s a nice way to augment what we have internally.

The iPhone app is doing quite nicely. I was quite pleasantly surprised. It feels very different [from the Web version]. It’s kind of amazing you can get this thing out of your pocket and type in and get stuff back that, if you showed it to a technical person from years ago, they would think it’s a bizarre, impossible object.

Another big direction which has taken off much more quickly than I expected is … Next Page »

Gregory T. Huang is Xconomy's Deputy Editor, National IT Editor, and the Editor of Xconomy Boston. You can e-mail him at gthuang@xconomy.com. Follow @gthuang